| 1 | Multi-Span and Multiple Relevant Time Series Prediction Based on Neighborhood Rough Set显示文摘Rough set theory has been widely researched for time series prediction problems such as rainfall runoff.Accurate forecasting of rainfall runoff is a long standing but still mostly signicant problem for water resource planning and management,reservoir and river regulation.Most research is focused on constructing the better model for improving prediction accuracy.In this paper,a rainfall runoff forecast model based on the variable-precision fuzzy neighborhood rough set(VPFNRS)is constructed to predict Watershed runoff value.Fuzzy neighborhood rough set dene the fuzzy decision of a sample by using the concept of fuzzy neighborhood.The fuzzy neighborhood rough set model with variable-precision can reduce the redundant attributes,and the essential equivalent data can improve the predictive capabilities of model.Meanwhile VFPFNRS can handle the numerical data,while it also deals well with the noise data.In the discussed approach,VPFNRS is used to reduce superuous attributes of the original data,the compact data are employed for predicting the rainfall runoff.The proposed method is examined utilizing data in the Luo River Basin located in Guangdong,China.The prediction accuracy is compared with that of support vector machines and long shortterm memory(LSTM).The experiments show that the method put forward achieves a higher predictive performance. | Xiaoli Li Shuailing Zhou Zixu An Zhenlong Du | 2021 | Computers, Materials & Continua2021，，6： | 1 |
| 2 | Bus travel time reliability incorporating stop waiting time and in‑vehicle travel time with AVL data显示文摘Improving bus travel time reliability can attract more commuters to use bus transit,and therefore reduces the share of cars and alleviates trafc congestion.This paper formulates a new bus travel time reliability metric that jointly considers two stochastic processes:the in-stop waiting process and in-vehicle travel time process,and the bus travel time reliability function is calculated by the convolution of independent events’probabilities.The new reliability metric is defned as the probability when bus travel time is less than a certain threshold and can be used in both conditions with and without bus transfer.Next,Automatic Vehicle Location(AVL)data of the city of Harbin is used to demonstrate the applicability of the proposed method.Results show that factors such as weather,day of the week,departure time,travel distance,and the distance from the boarding stop to the bus departure station can signifcantly afect the travel time reliability.Then,a case with low bus departure frequency is analyzed to show the impact of travelers’arrival distribution on their bus travel time reliability.Further,it is demonstrated that the travel time reliabilities of two bus transfer schemes of the same Origin–Destination(O–D)pair can have signifcantly diferent patterns.Understanding the bus travel time reliability pattern of the alternative bus routes can help passengers to choose a more reliable bus route under diferent conditions.The proposed bus travel time reliability metric is tested to be sensitive to the efect of diferent factors and can be applied in bus route recommendation,bus service evaluation,and optimization. | Zixu Zhuang Zhanhong Cheng Jia Yao Jian Wang Shi An | 2022 | International Journal of Coal Science & Technology2022，9，5： | 0 |
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